Agriculture


Utilization of Remote Sensed Data for Field Verification in the SMART Program

This project received a status update on : View Update.
View the final report of the project - Utilization of Remote Sensed Data for Field Verification in the SMART Program.

Principal Investigators

  • J. G. Thomas, Leader and Specialist, Extension Agricultural Engineering
  • M. A. Blaine, Extension Soybean Specialist, Plant and Soil Science


The purpose of this project is to use remote sensed data in conjunction with the SMART (Soybean Management by Application of Research and Technology) program which was initiated in Mississippi in 1992. All fields in the program are scouted at least once weekly and irrigated fields are scouted twice weekly during the growing season. In field scouting, for problems due to diseases, insects, weeds, soil fertility, moisture stress, etc. will be monitored. Increased emphasis on the effects of plant diseases and land forming will be included in this project. The SMART fields that are used in this project are already scouted weekly and is felt that ground truthing of remotely sensed data would help verify problems on a production field basis. From previous work that has been done in selected fields it is felt that problems in the fields could be identified quicker and easier if an area of stress can be identified and geo-referenced so scouting can focus on specific areas within a field. The results from this study will help identify what plant stresses are occurring in the areas identified from the remotely sensed data and the study will determine if the data can be generated with a quick enough turn around (flight to field use) to be useful in field production situations. Using geo-referenced data will allow GPS systems to be used to find the areas quicker and more accurately thus reducing scouting time and increasing scouting accuracy.

This will be a production field evaluation for remotely sensed data to determine if the technology is accurate, timely and economical enough for commercial agriculture applications. The multi-spectral images that are geo-referenced will be used to find areas in the field that are stressed or have different growth patterns due to diseases, insects, fertility, plant stands, soil variations and elevation. There will also be an economic analysis of the cost of random scouting versus geo-referenced scouting done. This will include cost of technology that is available and time saved and its relationship to the accuracy of a conventional scouting program.


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